Abstract
Society is experiencing a significant aging over the next few decades [1]. This will result in an increase by 30% more elderly and retired people and an increase of 100% in the number of people above 85 years of age. This increase in age will require significant new services for managed care and new facilities for providing assistance to people in their homes to maintain a reasonable quality of life for society in general and elderly and handicapped in particular. There are several possible solutions to the aging problem and the delivery of the needed services. One of the potential solutions is use of robotic appliances to provide services such as cleaning, getting dressed, mobility assistance, etc. In addition to providing assistance to elderly it can further be envisaged that such robotic appliances will be of general utility to humans both at the workplace and in their homes, for many difierent functions.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
P. Wallace, AgeQuake: Riding the Demographic Rollercoaster Shaking BUsiness, Finance and our World. London, UK: Nicholas Brealey Publishing Ltd., 1999.ISBN 1-85788-192-3.
S. Thrun, “Probabilistic algorithms in robotics,” AI Magazine, vol. 21, pp. 93–110, Winter 2000.
P. Jensfelt, D. Austin, and H. I. Christensen, “Towards task oriented localisation,” in Intelligent Autonomous Systems-6 (E. Pagelle, F. Groen, T. Aria, R. Dillmann, and A. Stenz, eds.), (Venice, IT), pp. 612–619, IAS, IOS Press, July 2000.
M. Andersson, A. Orebäck, M. Lindström, and H. Christensen, Intelligent Sensor Based Robots, vol. 1724 of Lecture Notes in Artificial Intelligence, ch. ISR: An Intelligent Service Robot, pp. 291–314. Heidelberg: Springer Verlag, October 1999.
G. Fink, N. Jungclaus, F. Kummert, H. Ritter, and G. Sagerer, “A distributed system for integrated speech and image understanding,” in Intl. Symp on Artificial Intelligence, (Cancun, Mexico), pp. 117–126, 1996.
G. A. Fink, C. Schillo, F. Kummert, and G. Sagerer, “Incremental speech recognition for multi-modal interfaces,” in IEEE 24th Conf. on Industrial Electronics, (Aachen), pp. 2012–2017, September 1998.
J. Cassell, “A framework for gesture generation and interpretation,” in Computer Vision for machine interaction (R. Cipolla and A. Pentland, eds.), pp. 191–215, Cambridge University Press, 1998.
T. Sterner, J. Weawer, and A. Pentland, “Real-time american sign language recognition using desk and wearable computer based video,” IEEE-PAMI, vol. 20, pp. 1371–1375, Dec. 1998.
R. Cipolla, P. Hadfield, and N. Hollinghurst, “Uncalibrated stereo vision with pointing for a man-machine interface,” in IAPR workshop on machine vision application, (Tokyo), December 1994.
R. Cipolla, N. Hollinghurst, A. Gee, and R. Dowland, “Computer vision in interactive robotics,” Assembly Automation, vol. 16, no. 1, 1996.
M. Soriano, B. Martinkauppi, S. Huovinen, and M. Laassonen, “Skin colour modelling under varying illumination conditions using skin locus for selecting training pixels,” in Real-Time Image Sequence Analysis-RISA-2000(O. Silven and J. Heikkilæ, eds.), (Oulu, Finland), pp. 43–49, Infotech, Oulu University, August 2000.
Y. Bar-Shalom and T. Fortmann, Tracking and Data Association. New York, NY.: Academic Press, 1987.
L. R. Rabiner, “A tutorial on Hidden Markov Models and selected applications in speech,” IEEE Proceedings, vol. 77, pp. 257–286, February 1989.
S. Young, The HTK Book. Cambridge University, UK, 1995.
L. Petersson, D. Austin, D. Kragi’c, and H. Christensen, “Towards an intelligent robot system,” in Proceedings of the Intelligent Autonomous Systems 6, IAS-6, (Venice), pp. 704–709, July 2000.
K. Tarabanis, P. Allen, and R. Tsai, “A survey of sensor planning in computer vision,” IEEE Transactions on Robotics and Automation, vol. 11, no. 1, pp. 86–104, 1995.
S. Edelman, ed., Representation and recognition in vision. Cambridge, MA: The MIT Press, 1999.
D. Roobaert, “Improving the generalisation of Linear Support Vector Machines: an application to 3D object recognition with cluttered background,” in Proceedings of the International Joint Conference on Artificial Intelligence, IJCAI’99, Workshop on Support Vector Machines, pp. 29–33, 1999.
G. Hager, W. Chang, and A. Morse, “Robot feedback control based on stereo vision: Towards calibration-free hand-eye coordination,” IEEE Control Systems Magazine, vol. 15, no. 1, pp. 30–39, 1995.
W. Wilson, C. W. Hulls, and G. Bell, “Relative end-effector control using cartesian position based visual servoing,” IEEE Transactions on Robotics and Automation, vol. 12, no. 5, pp. 684–696, 1996.
E. Malis, F. Chaumette, and S. Boudet, “Positioning a coarse-calibrated camera with respect to an unknown planar object by 2 1/2D visual servoing,” in 5th IFAC Symposium on Robot Control (SYROCO’97), vol. 2, (Nantes, France), pp. 517–523, September 1997.
A. Bicchi and V. Kumar, “Robotic grasping and contact: A review,” in Proc. of the IEEE Int. Conf. on Robotics and Automation, pp. 348–353, 2000.
K. B. Shimoga, “Robot grasp synthesis algorithms: A survey,” International Journal of Robotics Research, vol. 15, pp. 230–266, June 1996.
D. Lowe, “Fitting parameterized three-dimensional models to images,” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 13, no. 5, pp. 441–450, 1991.
D. Koller, K. Daniilidis, and H. Nagel, “Model-based object tracking in monocular image sequences of road traffic scenes,” International Journal of Computer Vision, vol. 10, no. 3, pp. 257–281, 1993.
E. Marchand, P. Bouthemy, and F. Chaumette, “A 2D-3D Model-Based Approach to Real-Time Visual Tracking,” Technical reportISSN 0249-6399, ISRN INRIA/RR-3920, Unit’e de recherche INRIA Rennes, IRISA, Campus universitaire de Beaulieu, 35042 Rennes Cedex, France, March 2000.
P. Wunsch and G. Hirzinger, “Real-time visual tracking of 3D objects with dynamic handling of occlusion,” in Proceedings of the IEEE International Conference on Robotics and Automation, ICRA’97, vol. 2, pp. 2868–2873, 1997.
A. Miller and P. Allen, “Examples of 3D grasp quality computations,” in Proc. of the IEEE International Conference on Robotics and Automation, vol. 2, pp. 1240–1246, 1999.
L. Roberts, “Machine perception of three-dimensional solids,” Optical and Electroooptical Information Processing, 1965.
M. Fischler and R. Bolles, “Random sample concensus: A paradigm for model fitting with applications to image analysis and automated cartography,” Comm. ACM, vol. 24, pp. 381–395, 1981.
M. Abidi and T. Chandra, “A new efficient and direct solution for pose estimation using quadrangular targets: algorithm and evaluation,” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 17, pp. 534–538, May 1995.
D. DeMenthon and L. Davis, “New exact and approximate solutions of the three-point perspective problem,” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 14, pp. 1100–1105, November 1992.
R. Horaud, B. Conio, and O. Leboulleux, “An analytical solution for the perspective-4-point problem,” Computer Vision, Graphics and Image Processing, vol. 47, pp. 33–44, 1989.
R. Tsai, “A versatile camera calibration technique for high-accuracy 3D machine vision metrology using off-the-shelf TV cameras and lenses,” IEEE Journal of Robotics and Automation, vol. 3, pp. 323–344, 1987.
J. Yuan, “A general photogrammetric method for determining object position and orientation,” IEEE Transactions on Robotics and Automation, vol. 5, pp. 129–142, April 1989.
D. DeMenthon and L. Davis, “Model-based object pose in 25 lines of code,” International Journal of Computer Vision, vol. 15, pp. 123–141, 1995.
R. C. H. Araujo and C. Brown, “A fully projective formulation for Lowe’s tracking algorithm,” Technical report 641, The University of Rochester, CS Department, Rochester, NY, November, 1996.
J. Foley, A. van Dam, S. Feiner, and J. Hughes, eds., Computer graphics-principles and practice. Addison-Wesley Publishing Company, 1990.
S. Hutchinson, G. D. Hager, and P. I. Corke, “A tutorial on visual servo control,” IEEE Transactions on Robotics and Automation, vol. 12, no. 5, pp. 651–670, 1996.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2002 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Christensen, H.I., Kragic, D., Sandberg, F. (2002). Vision for Interaction. In: Hager, G.D., Christensen, H.I., Bunke, H., Klein, R. (eds) Sensor Based Intelligent Robots. Lecture Notes in Computer Science, vol 2238. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45993-6_4
Download citation
DOI: https://doi.org/10.1007/3-540-45993-6_4
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-43399-6
Online ISBN: 978-3-540-45993-4
eBook Packages: Springer Book Archive